The results show different age-related changes depending on the tissue and the activity considered, so there is no universal decline in proteasome function with age in female mice. Interestingly, exceptionally old mice displayed better maintained proteasome activities, suggesting that preserved 20S proteasome is associated with successful aging.Oxidized, damaged and misfolded proteins accumulate during aging and contribute to impaired cell function and tissue homeodynamics. Damaged proteins are degraded by cellular clearance mechanisms like the 20S proteasome. Aging relates to low 20S proteasome function, whereas long-lived species show high levels. However, contradictory results exist depending on the tissue or cell type and it is unknown how the 20S proteasome functions in exceptionally old mice. The aim of this study was to investigate two proteasome activities (caspase-like and chymotrypsin-like) in several tissues  and cells  from adult (28 ± 4 weeks,  Accumulation of damage in DNA, RNA and proteins is one of the universal features of aging. Whatever the causative agents and the source of the damage, increased molecular heterogeneity and the resulting impairment of functions at all levels of organization are hallmarks of aging ,2,3. In The two main protein degradation systems are the autophagy pathway through the lysosomes and the proteasome system . The proSeveral studies indicate decline of the 20S proteasome activity with age that depends on at least three different mechanisms: decreased proteasome expression, alterations and/or replacement of proteasome subunits and formation of inhibitory cross-linked proteins . PeptidaConversely, long-lived animals, such as long-lived bat species, show high expression levels of the 20S proteasome subunits. These are related to less accumulation of oxidized proteins and greater resistance to oxidative stress . SimilarTo gain further insight into the activity of the 20S proteasome in aging and longevity, the aim of the present work was to investigate two different proteasome activities (CT-like and C-like) in several tissues  and cells  from adult, old and exceptionally old BALB/c female mice.We used 30 female BALB/c mice (Mus musculus), purchased from Harlan Ibérica , at a young adult age (28 ± 4 weeks). The mice were specifically pathogen free as tested by Harlan and according to the Federation of European Laboratory Science Associations recommendations. In our animal facility, placed at the Faculty of Biology (UCM), they were housed at 6 ± 1 per cage and maintained at a constant temperature (22 ± 2 °C) in sterile conditions inside an aseptic air negative pressure environmental cabinet , on a 12/12 h reversed light/dark cycle (lights on at 8 pm). Mice had access to tap water and standard Sander Mus pellets  ad libitum. Diet was in accordance with the recommendations of the American Institute of Nutrition for laboratory animals.n = 12), old  and exceptionally old , which had aged in our animal unit under the above specified conditions from the adult age. Each age group category was formed by animals that had been purchased in the same set. The exceptionally old mice had naturally achieved healthy and successful aging, since the average life span for females of BALB/c mice strain in our animal house was 99 ± 5 weeks [This cross-sectional study, defined as a study that takes place at a single point in time, was performed simultaneously on mice of different ages, namely adult  and 7.2 mM β-mercaptoetanol. Cell debris was removed by centrifugation and protein concentration was assessed in the supernatant using the bicinchoninic acid Protein Assay Kit protocol .Peptides used for determination of proteasome CT-like and C-like activities were Succinyl-leucine-leucine-valine-tyrosine-7-Amino-4-Methylcoumarin (Suc-LLVY-AMC) and Carboxybenzyl-Leu-Leu-Glu-7-Amino-4-Methylcoumarin (Z-LLE-AMC), respectively. Suc-LLVY-AMC or Z-LLE-AMC were added to a flat-bottom 96-well plate at a final concentration of 25 µM or 150 µM, respectively, together with the tissue/cell lysates adjusted to different protein concentrations, depending on the tissue, in order to measure linear kinetics of proteasome activity and ensure saturation was not reached during the course of the assay, in a final volume of 200 µL in 1 M HEPES pH 8. Protein amounts used were 60 µg for heart; 20 µg for liver, axillary nodes and peritoneal leukocytes; 10 µg for lung; and 2 µg for kidney. All measurements were made in triplicate, and samples for comparisons were run in the same test. For each individual and proteasome activity measurement, a negative control was performed in duplicate by adding a specific inhibitor of proteasome activity (MG132) at a final concentration of 400 µM. To detect the activity of the 20S proteasome, ATP was not added to the reaction mixtures.The reading was performed in a plate reader with a 380 nm excitation filter and a 460 nm emission filter. The plate was incubated inside the fluorimeter for 50 min, and during this time, 25 reading cycles were performed, 1 cycle every 120 s. The respective activity in the presence of MG132 was subtracted from each sample to obtain the specific activity (fluorescence arbitrary units per time in seconds). Results were expressed as specific activity/mg protein.Trypsin-like activity was not measured due to high interference of non-proteasome mediated trypsin-like activities in biological samples where the proteasome was not purified ,27.p < 0.05 was used for post-hoc comparisons when variances were homogeneous, whereas its counterpart analysis Games-Howell set at the same significance level was used with unequal variances. Differences versus adult age are shown.Data are expressed as mean ± standard deviation (SD). The normality of the samples and the homogeneity of variances were checked by the Kolmogorov–Smirnov and Levene analyses, respectively. Differences due to age were studied through the one-way analysis of variance. The Tukey test with a level of significance set at p < 0.05). Axillary lymph nodes showed unchanged values with age . Exceptionally old mice exhibited similar C-like activities to adults in lung (275.08 ± 63.90), liver (242.38 ± 46.56) and kidney (308.95 ± 65.25), plus axillary lymph nodes. Like old mice, exceptionally old mice showed lower (56.38 ± 9.66) C-like activity in heart (p < 0.01) and higher (198.33 ± 72.06) in peritoneal leukocytes (p < 0.05) than adults.p < 0.01). Conversely, old mice had higher CT-like activity in liver  and peritoneal leukocytes  than adult mice . No differences were found in heart and axillary lymph nodes with age . Exceptionally old mice showed similar CT-like activity to adults in lung (826.51 ± 198.39) and peritoneal leukocytes (473.36 ± 370.80). Likewise, exceptionally old mice had unchanged CT-like activity in heart and axillary lymph nodes with respect to adults. CT-like activity showed similar trends to old in exceptionally old age in kidney (509.60 ± 307.95) and liver (162.26 ± 46.62) with lower (p < 0.01) and higher values (p < 0.001) respectively, compared to adult mice.The present study shows relevant and complex age-related changes in C-like and CT-like activities of the 20S proteasome. These changes show strong particularities depending on the organ and peptidase activity considered. Some proteasome activities were lower in old mice in comparison with adult mice, such as the C-like activity in lungs and heart, and the CT-like activity in lungs and kidney. These results are in agreement with previous studies ,29 and wHowever, other proteasome activities were higher in old mice in comparison with adults, such as the C-like activity in liver, kidney and peritoneal leukocytes and the CT-like activity in liver and peritoneal leukocytes, in agreement with some previous studies ,30. The The net differential degree of age-related oxidative stress affecting tissues may be a relevant source of tissue-specific differences. Indeed, under normal conditions, the greater the proteasome activation, the greater the oxidative stress. However, if the oxidative stress is too high, the proteasome may be inhibited ,36. AddiOf note, our observations do not ascertain the underlying mechanisms responsible for the age-related changes in 20S proteasome activities, e.g., proteasome subunit expression, translation and/or assembly, and/or regulation of activity by, for example, formation of inhibitory complexes . Future Overall, exceptionally old mice had similar peptidase activities to adult mice in most tissues investigated, suggesting that preserved 20S proteasome function correlates with achieving extreme old age. Exceptionally old mice showed lower C-like activity in the heart and CT-like activity in the kidney, and higher CT-like activity in the liver and peritoneal leukocytes, in similar trends to old mice. Lower activities in exceptionally old animals may suggest relatively disposable functions in the context of reaching successful aging, whereas higher/preserved activities could reflect adaptive mechanisms underlying healthy aging. Consistent with this idea, longevity was associated with higher CT-like activity in liver of naked mole rats compared to shorter-lived mice . These iAs an additional limitation of our study, proteasome activities were only investigated in female mice. Female mice were prioritized over males to promote research on females, because of the ease of caging them together as mice are a social species, and because females of virtually all species including mammals live longer than males ,41,42. TIn fact, a pulse of estrogen in ovariectomized mice aimed at mimicking late diestrus II/early proestrus, stimulated the turn-over of certain proteins, including estrogen receptor alpha and 20S proteasome chymotryptic activity in mammary glands in vivo . In mammTogether, our data show unique patterns of age-related changes in the 20S proteasome activity and no universal decline in old female mice. Exceptionally old female mice displayed well-preserved 20S proteasome activities. Although further analyses are needed to evaluate the role of the 20S proteasome during the aging process, our study provides evidence that exceptionally old mice have sustained activity which may help achieve successful aging.


Schizochytrium sp., as a promising feed additive, on the antioxidant enzyme activity, physicochemical quality, fatty acid composition and volatile compounds of beef. The results revealed that Schizochytrium could improve the antioxidant capacity of beef and increase the nutritional value, which was related to the abundant docosahexaenoic acid (DHA) found in Schizochytrium. Our current research results provide guidance for the development of environmentally friendly diet additives.This study evaluated the effects of Schizochytrium sp.) containing docosahexaenoic acid (DHA) on the antioxidant enzyme activity, physicochemical quality, fatty acid composition and volatile compounds of beef meat. Eighteen male Qaidamford cattle were randomly allocated into three treatments (n = 6): no micro-algae supplementation , 100 g microalgae supplementation per bull per day (FD1), and 200 g microalgae supplementation per bull per day (FD2), and fed for 49 days before slaughter. The results showed that, compared with the C group, the addition of DHA-rich microalgae to the diet could significantly increase the total antioxidant capacity (T-AOC) in meat. In the FD2 group, it was found that the concentration of glutathione peroxidase (GSH-Px) was significantly higher than that of the control group (p < 0.05). DHA-rich microalgae supplementation increased polyunsaturated fatty acid (PUFA), eicosapentaenoic acid , DHA, EPA + DHA, and n-3 PUFA and reduced n-6:n-3 fatty acid ratio. Twenty-four volatile compounds identified in beef were mainly aldehydes, alcohols and ketones from the fingerprints. The contents of short-chain fatty aldehydes, 1-octen-3-ol and 2-pentylfuran, were higher in the FD2 group than in the other two groups. The microalgae diet improved the sensory attribute score of beef. The results demonstrated that dietary supplementation of DHA-rich microalgae improved the antioxidant status, increased the deposition of DHA and enhanced the characteristic flavor of beef.The purpose of this study was to evaluate the effects of dietary supplementation with microalgae ( The beef industry has become one of the fastest-growing industries in China’s animal husbandry . Beef coSchizochytrium is a kind of thraustochytrid microalgae, and is the source of DHA in the marine food chain [Schizochytrium in animal diets has been proven to improve the quality of meat and increase the content of n-3 PUFA [Researchers found that after animals were fed fish oil, the oxidative stability of the meat was reduced and was accompanied by off-odors, which was caused by the oxidation of lipids in the meat during shelf life ,9,10. Anod chain . The addn-3 PUFA ,21,22,23Schizochytrium addition. Therefore, the purpose of this study is to determine the influence of a dietary DHA-rich microalgae concentration through the determination of antioxidant capacity, physical indicators, fatty acid composition and volatile compounds.We hypothesized that the difference in antioxidant status and volatile compounds in beef after slaughter could be explained by the level of Schizochytrium sp. powder and then ingested the dietary roughage mixed with oat hay and alfalfa hay. The ratio of forage to concentrate was 60:40. The ingredient and chemical composition of the basal diets are presented in A total of 18 male Qaidamford cattle  were randomly allocated to three experimental groups with 6 bulls of each, and assigned to individual pens (3 × 2.5 m). The experiment lasted for 49 days. This research was conducted in Qinghai Jinsui Animal Husbandry Co., Ltd. . All animals were fed twice daily at 08:00 h and 17:00 h. Water was provided freely. The experimental groups were as follows: (1) C , (2) FD1  and (3) FD2 . The bulls first received the concentrate mixed with the Schizochytrium sp. used in the diets is shown in Schizochytrium sp. powder  was purchased from Xi’an Xiaocao Biotechnology Co., Ltd. .The crude protein, calcium and phosphorus contents of the experimental diet were analyzed following the Association of Official Analytical Chemists’ (AOAC) methods . The conM. longissimus lumborum (LL) muscle sample was taken from the left side of each carcass and transported to the laboratory with a portable cooler. All beef samples were trimmed with visible fat and connective tissue before vacuum packaging and stored at −80 °C for further analysis within two weeks. All animals were weighed  and transported to commercial slaughterhouses for slaughter to facilitate sample collection and measurement after the end of the feeding trial. In order to better simulate the quality of beef consumed by residents in the Qinghai-Tibet Plateau, we chose 48 h after slaughter as the sampling time. After chilling for 48 h at 4 °C, the w/v) and then homogenized with Ultra Turrax T25  homogenizer. After centrifugation at 4000 rpm and 4 °C for 10 min, the supernatant was collected to determine the protein content and antioxidant enzyme activity. Protein concentration, total antioxidant capacity (T-AOC), superoxide dismutase (SOD), glutathione peroxidase (GSH-Px) levels and thiobarbituric acid reactive substances (TBARS) level were measured using commercial assay kits  by a spectrophotometer . The results of T-AOC, SOD and GSH-Px were expressed in U/mg protein, and the absorbance was measured at 520 nm, 550 nm and 412 nm, respectively. Lipid oxidation was evaluated using the TBARS value. The absorbance was measured at 532 nm. Results were expressed as mg malonaldehyde (MDA)/kg meat.All samples were thawed at 4 °C for 24 h before analysis. One gram of meat was mixed with cold phosphate-buffered saline  at a ratio of 1:10  calibrated with pH 4 and 7 standard buffer solutions. The average value obtained by inserting electrodes into three different points of each sample was used for statistical analysis.L* (lightness), a* (redness) and b* (yellowness) were measured at different positions on the surface of each sample with triplicate measurements, and the average values were calculated. Chroma (C*) and hue angle (H*) were evaluated by the following equations:The thawed LL muscle sample was bloomed for 45 min before measurement. The surface color of meat was measured with a portable CR-400 Colorimeter , using an illuminant D65 and a 2-degree standard observer. Color parameters Drip loss. Drip loss was estimated according to the protocol followed by Honikel . ApproxiCooking Loss. Cooking loss was determined as suggested by Fabre et al. . BrieflyApproximately 50 g of the minced meat sample was measured according to the method of the AOAC , in whic2SO4) in water and cooled to room temperature. After 1.5 h incubation, the mixture was cooled and then thoroughly mixed with 3 mL of hexane solvent and centrifuged. Approximately 1 mL supernatant  was transferred into an injection vial for analysis. The FAME was determined with the gas chromatograph , equipped with a detector (flame ionization), and separate SP-2560 type column (capillary) . The sample split ratio was 30:1. Gas chromatographic conditions were set according to Aldai et al. [The fatty acids composition analyses were carried out according to Ponnampalam et al. . In brieBeef samples were collected in triplicate for each group of volatile compounds. The volatile compounds were determined using a Flavorspec Gas Chromatograph-Ion Mobility Spectrometer (GC-IMS) system  fitted with a SE-54 capillary column (15 m × 0.53 mm), and conducted with modifications according to the methods of Xu et al. . BrieflyEight trained sensory panel members were selected according to the Chinese standard GB/T 22210-2008 . The samples were baked on a household grill at 185 °C and removed when the core temperature reached 70 °C. After cooking, each sample was cut into 1.5 cm cubes, placed on a paper plate with a three-digit number and then presented to the panelists. During testing, panelists were seated in a separate compartment in the sensory room. Before proceeding to the next round of evaluation, panelists were instructed to rinse their mouths with water to clear the taste between the samples. All sensory analyses were repeated three times. The sensory attribute score of each sample was divided into 8 levels: initial juiciness ; sustained juiciness ; flavor intensity ; off-flavor intensity ; initial tenderness ; sustained tenderness ; residue .p < 0.05.All the experiments were performed in triplicate. The collected data were analyzed using one-way analysis of variance (ANOVA) by the SAS 9.2 program . The Shapiro–Wilk test and Levene test were used to evaluate the normality of the data distribution and the homogeneity of variance. The Duncan test was used to compare mean values. Significant differences were declared at p < 0.05). No significant difference was observed in T-AOC and GSH-Px activities between the FD1 group and the FD2 group (p > 0.05). There was no significant difference in SOD activity and TBARS in all treatment groups (p > 0.05).Effects of dietary DHA-rich microalgae on the antioxidant enzyme activity of beef are shown in p > 0.05) in color parameters , pH, drip loss, cooking loss and protein among the three treatments. The fat content in the FD1 and FD2 groups was significantly higher than that in the control group (p < 0.05).The effects of dietary DHA-rich microalgae on physicochemical meat quality are presented in p > 0.05). Saturated fatty acids (SFA) in the FD1 and FD2 groups was greater (p < 0.05) than that in the control group. The cattle supplemented with DHA-rich microalgae had higher SFA (p = 0.007), PUFA (p = 0.001), n-3 PUFA (p < 0.001) and EPA + DHA (p < 0.001), and a lower (p < 0.001) n-6/n-3 ratio. Moreover, the concentrations of EPA, DHA, EPA + DHA and total n-3 PUFA increased significantly with increasing DHA-rich microalgae (p < 0.001). The relative proportion of EPA and DHA were 4–6 times and 8.5–11.4 times higher (p < 0.001) for FD1 and FD2 groups compared to the control group.The influences of dietary DHA-rich microalgae on fatty acids composition in the LL muscle of beef are given in p < 0.05) than that in the control group. DHA-rich microalgae increased the concentrations of C16:0 and SFA in the meat, which may be related to the higher contents of C16:0 and SFA contained in microalgae powder, which were difficult to be oxidized and easy to deposit [p < 0.05) than that in the control group, but there was no difference (p > 0.05) from that in the FD1 group.Diet also influenced individual fatty acid contents, whereas C16:0 and C18:3 n-3 (ALA) in the FD1 and FD2 groups was higher  scores of initial juiciness, sustained juiciness, flavor intensity, initial tenderness and sustained tenderness, and lower (p < 0.05) scores of residue. There was no observed effect of diet (FD1 or FD2) on off-flavor intensity (p > 0.05). However, the sensory scores between the FD1 and FD2 groups did not show a significant difference (p > 0.05).The mean scores for sensory evaluation of beef are presented in Schizochytrium contained some antioxidants such as β-carotene and vitamin E [Schizochytrium did not affect the SOD activity in the blood of calves. The content of TBARS is considered to be one of the most accurate indicators for evaluating lipid peroxidation [It is known that antioxidant capacity is an important factor in maintaining animal health . As a paitamin E . SOD diritamin E , while Gitamin E . In thisitamin E , who repxidation . Since lxidation . Our resSchizochytrium did not affect the animal meat color [Meat color is an important indicator for evaluating meat quality, which determines the consumers’ desire to buy . In the at color ,41,42. Tat color . Urrutiaat color  reportedat color , but it With the increase of DHA-rich microalgae supplemented in the diet, the contents of EPA, DHA, EPA + DHA and n-3 PUFA showed a linear increase. As expected, marine resources exhibited the ability to accumulate DHA and EPA contents in meat . There wVolatile alcohols, aldehydes and ketones belong to lipid-derived compounds . They arMost consumers believe that higher fat is related to greater eating satisfaction . This stSchizochytrium sp. At the same time, the supplementation of DHA-rich microalgae enhanced the volatile compounds in beef, especially in the high-dose FD2 group. It is necessary to conduct further research on the metabolites and oxidation mechanism of fatty acids in meat.In conclusion, adding different levels of DHA-rich microalgae to the diet could increase the activity of certain antioxidant enzymes in beef. Our results demonstrate that DHA and EPA levels in meat were enriched by supplementing DHA-rich microalgae. In addition, the reduced ratio of n-6/n-3 was another potential health benefit associated with algae in


Background and Objectives: Soluble cell adhesion molecules (sCAMs) play a significant role in the metastatic potential of breast cancer (BC). They might block lymphocytes and promote angiogenesis and migration of cancer cells. We assessed the usefulness of sCAMs in the prognosis and monitoring of the progression of advanced BC. Materials and Methods: We assessed soluble E-selectin, P-selectin, VCAM-1, ICAM-1, EpCAM, IL-6Ra, TNF-R1, and TNF-R2 in 39 women with aBC. Blood samples were obtained at the beginning of the treatment and after 2 months. Results: The median progression-free survival (PFS) was 9 months, and overall survival (OS) was 27 months. The higher levels of sICAM-1  and lower levels of sEpCAM  were associated with faster progression of aBC. High levels of sEpCAM through the follow-up period were significantly associated with a lower risk of progression . We found the independent predictive value of higher than median sICAM-1 levels for PFS  and of sVCAM-1 levels for OS . Conclusions: Our data support the predictive value of sICAM-1 and sVCAM-1 and suggest that they could become markers for tailoring new therapies in aBC. sEpCAM level could be used as an early indicator of response to the therapy. Breast cancer (BC) is the most common malignancy and one of the leading causes of cancer death among women worldwide. The global incidence of BC is estimated at over 2 million in 2020 . The incCell adhesion molecules (CAMs) are a group of proteins that play a significant role in the metastatic potential of BC cells . In physCAMs are physiologically bound to the cell membrane, and after cleavage, soluble forms can be detected in the circulation  . In cancE-selectin and P-selectin are adhesive molecules with a glycoprotein structure that consists of intracellular cytoplasmic tail, a transmembrane domain, and an extracellular C-type lectin-like domain, an epidermal grows factor-like domain and homological to complement control protein, which differs between selectins . E-selecICAM-1 and VCAM-1 are members of the immunoglobulin superfamily, and both mediate the adhesion of leukocytes to vascular endothelium . EpCAM iContrary, the function of the soluble forms of CAMs is poorly understood. It was suggested that the shedding of sCAM might enhance metastasis by binding and blocking cytotoxic lymphocytes . AdditioTherefore, the main goal of the study was to assess the usefulness of the above-mentioned sCAMs in the prediction and monitoring of the response to the therapy of advanced breast cancer (aBC).n = 3), venous thrombosis (n = 2), infections (n = 3), and hemolysis in the first blood specimens (n = 2). One of the patients had more than one exclusion criteria. Finally, 39 women were included in the analysis.The study involved 48 unselected Caucasian women with aBC treated in the Department of Internal Diseases and Oncological Chemotherapy, the Medical University of Silesia in Katowice, from July 2014 to September 2019. An inclusion criterion was histologically confirmed aBC . The exclusion criteria were as follow: a history of autoimmune disease , tamoxifen (n = 3), fulvestrant (n = 2)), 4 women shortly after the start of therapy , and 1 woman without treatment, qualified for watchful waiting. The second blood sample collection was obtained after 2 months from the first assessment (before the subsequent cycle among treated with chemotherapy). All patients had undergone physical examination and assessment of laboratory parameters before each treatment cycle or visit. Computed tomography or ultrasonography was performed generally every 3 months to assess the treatment efficacy, and the best responses were documented according to the Response Evaluation Criteria in Solid Tumours version 1.1 (RECIST ver 1.1) [The first peripheral blood samples were obtained from 34 women before initiation of therapy (ver 1.1) . The colThe study was approved by the Bioethics Committee of the Medical University of Silesia in Katowice . Written informed consent was obtained for each patient.Five milliliters of peripheral blood was collected in BD Vacutainer Tubes. Obtained blood samples were immediately centrifuged at 3000 rpm for 10 min to obtain serum, then transferred to tubes and immediately stored in the liquid nitrogen.Serum levels of soluble forms of E-selectin, P-selectin, VCAM-1, ICAM-1, EpCAM, Interleukin-6 Receptor subunit alpha (IL6Ra), Tumor Necrosis Factor Receptor 1 (TNF-R1), Tumor Necrosis Factor Receptor 2 (TNF-R2) were measured via multiplex technique , following the manufacturer’s instruction. Bead fluorescence readings were taken using the Bio-Plex 200 System  using high PMT (High RP1) setting and analysed with Bio-Plex Manager version 6.1.0.727 .The diagnosis of diabetes was based on fasting serum glucose above 125 mg/dL on two separate tests  or medicThe body mass index (BMI) was calculated as the weight (kg) divided by the square of the height (meters).Rapid disease progression (RDP) was defined as progression occurring within 6 months from the start of the study.http://www.R-project.org/ accessed on 17 November 2021). Statistical significance was set at a p-value below 0.05. All tests were two-tailed. Imputations were not performed for missing data. Nominal and ordinal data were expressed as percentages. Interval data were expressed as the mean value ± standard deviation in the case of normal distribution. In the case of data with skewed or non-normal distribution, they were expressed as the median, with lower (Q1) and upper (Q3) quartiles. The distribution of variables was evaluated by the Anderson–Darling test and the quantile-quantile (Q–Q) plot. Homogeneity of variances was assessed by the Levene test. Nominal and ordinal data were compared with the χ2 test. Comparisons between groups for interval data and also for longitudinal data were conducted with mixed models . The post hoc tests were performed with one-way variance analysis (ANOVA), with the Benjamini–Hochberg correction for multiple testing. Overall survival, as well as progression-free survival, were analysed with the Cox proportional regression models and shown with hazard ratios (HR), corresponding confidence intervals (±95% CI), and p-values. We used either the baseline values divided below and above the median (Model 1), standardised values (Model 2), or the time-depended values. The proportionality assumption was tested based on the Schoenfeld residuals (R function cox.zph). Multiple-collinearity was checked based on the correlation matrix of coefficients of the survival model. Additionally, PFS was performed with Kaplan–Meyer curves, stratified by median values, with the log-rank test to compare survival curves. The associations between variables were assessed with the Spearman ranks correlation coefficient.Statistical analyses were performed using STATISTICA 13.0 PL , StataSE 13.0 , and the R software (R Core Team (2013), R Foundation for Statistical Computing, Vienna, Austria, The study group consisted of 39 women with aBC aged between 39 and 85 years (average age 60 ± 11 years), and significant comorbidity including hypertension (66.7%), type 2 diabetes (28.2%), and obesity (15.4%)—A greater percentage of patients were diagnosed with hormone-receptor-positive/HER2 negative (HR+/HER2−) breast cancer (66.7%), with metachronous metastases (64.1%) and multiple organs metastases (76.9%). The most common sites of metastases were bones (53.8%) and lungs/pleura (51.3%). Seventeen of 26 patients (65.4%) with HR+/HER− aBC started chemotherapy after progression on hormone therapy.Anticoagulant prophylaxis and bisphosphonates were prescribed in 35.9% and 30.8% of patients, respectively.During the follow-up period, the disease progression occurred in 31 (79.5%), and 28 (71.8%) died due to metastatic breast cancer. The rapid disease progression was observed in 17 (43.6%) patients. The median time of progression-free survival (PFS) was 9 months (quartiles: 4–34), and overall survival (OS) was 27 months (quartiles: 14–44).The median serum soluble adhesion molecules (sCAMs) concentrations at baseline and after 2 months of follow-up are shown in p < 0.01; ρ = 0.36, p < 0.05; ρ = 0.45, p < 0.01, respectively), while moderate negative one with sTNF-R2 . In addition, from moderate positive correlations between sEpCAM and sE-Selectin, sIL-R6a and sTNF-R1 levels were found  and between sEpCAM and sP-selectin as well as sIL-6Ra .In the case of relative changes in the initial value, the moderate positive correlations between sVCAM-1 and sTNF-R1 as well as sTNF-R2 were found  declined the risk. Other factors were insignificant .In parallel, the log-rank analysis of Kaplan–Meier survival curves performed for the significant biomarkers mentioned above showed that patients with levels above the median of sICAM-1 (>388.5 ng/mL), sVCAM-1 (>624.6 ng/mL), and sTNF-R2 (>1.95 ng/mL) had significantly shorter PFS than patients with lower levels .p < 0.05) and sICAM-1 (p = 0.08) increased more than twice the risk of progression. On the contrary, in the second one, the occurrence of liver metastasis maintained the predictive value (p = 0.08). Moreover, the time-dependent Cox model showed that high levels of sEpCAM through the follow-up period were significantly associated with a lower risk of progression .Cox proportional hazards models for PFS were used with independent factors selected based on the univariable analysis . The mulp = 0.08).The univariable analysis showed that occurrence of liver and multiple organ metastasis was associated with a greater risk of progression, brain metastasis, higher grading, and sVCAM-1 levels above-median were of borderline significance. On the contrary, the HER2 overexpression combined with targeted treatment (trastuzumab ± pertuzumab) declined the risk. Other factors were insignificant . In paraCox proportional hazards models for OS were used based on factors selected in the univariable analysis . The mulp < 0.01). The higher levels of sICAM-1  and lower levels of of sEpCAM  were associated with fast progression. The mixed model’s analysis with repeated measurements showed that there is a significant effect of slow/fast progression and time for sEpCAM levels (p < 0.001), with significant interaction. The post hoc adjusted analysis revealed that sEpCAM levels diminished through the follow-up period only in slow progressors (1029 (757–1442) vs. 575 (495–909); p < 0.05). Moreover, at baseline, they had higher levels than fast progressors (607 (443–744), p < 0.01). No difference was observed after a 2 month follow-up period.There were 17 (43.6%) fast progressors in the study group, and they had more than 3-times higher risk of death  showed that although the higher levels of sICAM-1 and sTNF-R2 above the median, as well as sICAM-1 standardised levels, lost a statistical significance, yet kept a predictive direction for PFS . Similarly, in case of OS the sVCAM-1 levels kept its predictive direction .The sub-analysis of luminal HER2-negative aBC  could be damage of endothelium by cytotoxic chemotherapeutics. Similar results were observed in the group of patients with early BC receiving adjuvant chemotherapy. Mills et al.  showed eThese cell adhesion molecules are located primarily on the surface of the endothelium and cells of the immune system. CAMs expression is induced by cytokines such as TNF-α . HoweverTo the best of our knowledge, this study was the first that investigated the association between levels of sEpCAM and survival in patients with aBC. Karabulut et al.  conducteIn summary, we confirmed the prognostic value of sICAM-1 and sVCAM-1 in patients with aBC. In addition, we evaluated the changes in the serum levels of sCAM, and similar to the first, we found the association between time of progression and changes in sEpCAM levels. However, we observed an increase in sICAM-1 and sVCAM-1 during the treatment, largely based on CTH. Thus, the usefulness of these sCAM as a marker of response to chemotherapy is limited.This study has some limitations, mostly related to the size of our single-centre cohort. In consistence with the cancer statistics, most of our patients had luminal cancer subtypes, and therefore we restricted sensitivity analysis to this subtype. We cannot exclude that sCAM profile and its prognostic value might be different for non-luminal subtypes of aBC. Only a multicenter study can investigate sCAMs profile in patients with all breast cancer subtypes and assess its prognostic value. This problem might also be solved by access to samples collected and stored during previously performed studies. Thus, performing assessments in the stored samples may also overcome the limitations of our study.In addition, the study was conducted when CDK4/6 inhibitors were not available outside clinical trials. Most patients with HR+/HER2− cancer received chemotherapy after failure of adjuvant hormone therapy. Currently, CDK4/6 inhibitors are the main therapeutic option in the treatment of luminal HER2 negative aBC as the first-line or second-line . Further(1) Our data support the predictive value of sICAM-1 and sVCAM-1 and suggest that they could become markers for tailoring new therapies in aBC;(2) Serum sEpCAM levels might have a diagnostic role in patients with aBC and be used as an indicator of response to CTH. Additionally, it could be helpful to identify patients with luminal breast cancer who will have the benefit from chemotherapy.However, we have stressed that this study has a preliminary nature. These hypotheses require confirmation in a much larger multicenter clinical trial.


Colletotrichum scovillei causes anthracnose of chili pepper in many countries. Three strains of this pathogen, Coll-524, Coll-153, and Coll-365, show varied virulence on chili pepper. Among the three strains, Coll-365 showed significant defects in growth and virulence. To decipher the genetic variations among these strains and identify genes contributing to growth and virulence, comparative genomic analysis and gene transformation to show gene function were applied in this study. Compared to Coll-524, Coll-153, and Coll-365 had numerous gene losses including 32 candidate effector genes that are mainly exist in acutatum species complex. A cluster of 14 genes in a 34-kb genomic fragment was lost in Coll-365. Through gene transformation, three genes in the 34-kb fragment were identified to have functions in growth and/or virulence of C. scovillei. CsPLAA encoding a phospholipase A2-activating protein enhanced the growth of Coll-365. A combination of CsPLAA with one transcription factor CsBZTF and one C6 zinc finger domain-containing protein CsCZCP was found to enhance the pathogenicity of Coll-365. Introduction of CsGIP, which encodes a hypothetical protein, into Coll-365 caused a reduction in the germination rate of Coll-365. In conclusion, the highest virulent strain Coll-524 had more genes and encoded more pathogenicity related proteins and transposable elements than the other two strains, which may contribute to the high virulence of Coll-524. In addition, the absence of the 34-kb fragment plays a critical role in the defects of growth and virulence of strain Coll-365. Capsicum spp.) is a globally significant spice crop. The cultivation of chili pepper is frequently threatened by the attacks of various pathogens, especially the anthracnose pathogens of the Colletotrichum species. Colletotrichum contains a large number of species members that have been classified into several species complexes , indicating no delay in the penetration step for Coll-365 compared to Coll-524 and Coll-153. The three strains can grow into the cuticle layer of chili pepper fruit at 24 hpi and form a highly branched structure (HBPS) within the cuticle layer and penetrate epidermal cells at 72 hpi  variations and successfully identified DNA fragments involved in the defects in growth and virulence of Coll-365. Moreover, by gene transformation we have demonstrated four genes that display function in germination, growth and/or virulence in the chili pepper pathogen C. scovillei strain Coll-365.In this study, to decipher the genetic variations of the three Colletotrichum strains Coll-524, Coll-153, and Coll-365 were obtained from the AVRDC-The World Vegetable Center  as mentioned in a previous study  for 6 days at 25°C with a 12 h light/dark cycle. Spores were collected and used for general cultivation, assays of germination and appressorium formation, morphological examination, growth, and pathogenicity assay.Three us study . For spo5 spores/ml) at 25°C with shaking at 200 rpm for 1 day. The young hyphae were collected by filtrating with a layer of miracloth. The DNA was extracted from the young hyphae using the CTAB extraction method  and the sordariomyceta_odb10 dataset  were used for phylogenetic analyses . The seqColletotrichum fioriniae PJ7 (PRJNA244481) was provided to MAKER for the “EST evidence” and “Protein Homology Evidence” functions respectively. The gene annotation of Coll-153 and Coll-365 was conducted using the same method as that for Coll-524. The CDS region of each gene was extracted from the genome sequence according to the GFF file which was originated from MAKER by GffRead (Gene annotation was conducted using MAKER (v.2.31.10)  pipeline GffRead . Gene anE-values lower than 10 were selected according to the default setting of the PHIB-BLAST web server. The protein sequences of all annotated genes of Coll-153, Coll-365, and Coll-524 were used for ortholog analysis with the default settings of OrthoFinder  to obtain the information about gene function. To find effector candidates, protein sequences of the three strains were analyzed by EffectorP 2.0 . CarbohyhoFinder . After t3. The transposon element sequences were acquired according to the GFF files provided by Transposon PSI. These sequences were further extracted to create a Transposon element database (TED). RepeatModeler was used for de novo genome-wide repeat family analysis , Insertion, Deletion and Removed, which are specified by CLC with default setting. Briefly, “Deletion” is for positions where a gap is called while the reference has a non-gap; “Insertion” is for positions where a non-gap is called while the reference has a gap; “Removal” is for positions where no reads are mapped to the reference; “Misc. difference” is for every position where the consensus is different from the reference. The Misc. difference dataset consisted of single nucleotide polymorphism (SNP) and polymorphism with more than one nucleotide, which was named as multiple nucleotide polymorphism (MNP) in this study. The four datasets were combined to generate the genome sequence variations and used for genome comparisons to identify ORF variations between Coll-524 and the other two strains as described in Open reading frame variation analysis was based on the calculations of physical position overlapping between each ORF and the four datasets of variations . The GFF file generated by MAKER could provide the physical positions of mRNA, exon, 5′UTR, CDS, 3′UTR for each gene. A gene usually contains multiple CDSs in eukaryotes and all CDSs together within the gene is the complete coding sequence to translate a protein encoded by the gene. To analyze ORF variation of Coll-153 and Coll-365, the ORF position of each Coll-524 gene was generated by setting the first nucleotide of the first CDS as the beginning position and the last nucleotide of the last CDS as the end position.To analyze the variation of each ORF between Coll-524 and the other two strains, firstly, all scaffolds of Coll-524 were added together one by one to form a single sequence. The physical positions of each ORF were modified to fit into the single sequence. The four datasets of variations  generated by CLC were tagged with physical positions in each scaffold of Coll-524. Therefore, the second step was to edit the physical positions of each variation according to the single genome sequence of Coll-524. The position differences of each variation to the ORF were compared and calculated as indicated in E-value < 10e-50). Finally, were ORFs with <50% coverage to Coll-153 and/or 365 according to the blastn results. Genes with the four criteria were analyzed by Venn Diagram4. Pathogen–host interaction related genes were selected with an E-value less than 10e-50. Genes with an E-value less than 10e-50 but greater than 10e-100 were considered to have almost identical sequences to the database according to the manual for CLC Genomics Workbench 9.5.To select genes for genetic analysis to verify their functions on the defects of growth and virulence of Coll-365, four selection criteria were set for gene selection. First were ORFs predicted to be ORF-V. Second were “Coll-524 extra genes” according to the result of OrthoFinder analysis. Third were genes analyzed to belonging to candidate effector, CAZyme, TF, SMURF, enzyme or PHI , and DNA ligation. Plasmid BsBR was modified from pBsHR by replacing (HygR) with bleomycin resistance gene (BleoR) of pAN8-1  and ligated to EcoRV or SwaI digested and Shrimp Alkaline Phosphatase (rSAP) treated pBsHR. If double gene-transformation was needed, a second target gene was cloned in to pBsBR for protoplast transformation and phleomycin was used as the selection antibiotic (Plasmids BsHR and BsBR were constructed and used in this research to clone the selected target gene(s) for transformation into Coll-365. pBsHR was constructed by cloning hygromycin resistance cassette (HygR) of pBHt2  into pBlf pAN8-1 . The Bletibiotic . For gen+2-mediated protoplast transformation was used to transfer the target gene to Coll-365. Spores collected from a 6-day MS agar medium were inoculated into a 500-ml flask containing 400 ml MS liquid medium and a stirrer bar, and cultured for 16 h under 25°C at low speed to prevent the attachment of spores to the flask surface. The young hyphae were collected by filtering through a layer of miracloth and washed with 100 ml sterilized water and 100 ml wash buffer (1 M NaCl and 10 mM CaCl2) under suction. The washed hyphae (250 mg) were then resuspended in a 50-ml flask containing 10 ml osmotic buffer  with 90 mg lysing enzymes , and incubated in an orbital shaker with 150 rpm at 30°C for 6 h. The undigested hyphae were removed by filtering through miracloth and the protoplasts were collected by centrifugation at 1500 g, 4°C for 10 min. The protoplasts were resuspended by adding 100 μl mixture of four parts of STC buffer  and one part of PEG . For transformation, 20 μl of 20 μg plasmid DNA was added to a tube containing 100 μl protoplast suspension with gentle mixing and the mixture was placed in ice for 20 min. PEG was added into the DNA-protoplast solution four times with different volumes. The adding steps were performed by following a previous description (3)2⋅4H20, 1.5 mM KH2PO4, 1 mM MgSO4⋅7H2O, 2.5 mM NaCl, 60 mM glucose, and 1 M sucrose] was added into the PEG-DNA-protoplast mixture and cultured at 25°C for 16 h with 100 rpm shaking. The protoplasts were collected with centrifugation at 25°C, 1800 g for 10 min. A total of 300 μl regenerated protoplasts were obtained and then evenly spread on three regeneration agar medium plates. After incubation for 6–8 days at 25°C, the transformants were isolated, single spore purification and PCR verification for the target gene insertion.Polyethylene glycol (PEG)/Cacription  with sliMW073123) was used as the control for PCR assay. To verify gene transformation of transgenic Coll-365 strains, regular PCR and RT-PCR assays were performed. Regular PCR using genomic DNA as template to amplify the transgenic gene was used for all transgenic strains. For transgenic strains carrying more than one transgene, RT-PCR assays were conducted in addition to the regular PCR. Primers used in theses assays are listed in 5 spores/ml) at 25°C with shaking at 150 rpm for 2 days. The hyphae were collected by filtrating with a layer of miracloth. The RNA was extracted with Trizol reagent (Invitrogen). RNA purity and concentration were determined and cDNA was synthesized using 5 μg RNA and the MMLV reverse transcription kit (Invitrogen). PCR was performed using 20 μl reaction volume contained 1 × PCR Buffer, 0.2 mM dNTP, 0.4 μM primers, 1 U Blend Taq plus (TOYOBO), and 1 μl of template DNA. PCR reaction was performed as follows: 94°C for 2 min and 25 cycles of 94°C for 30 s, 60°C for 30 s, and 72°C for 3 min. The PCR products were analyzed by agarose gel electrophoresis.Eight genes were selected for functional assay in Coll-365 as listed in 5 spores/ml by sterilized water. For growth assay, a 5-μl, spore suspension containing 500 spores was dropped on the center of MS agar medium plate and incubated for 6 days at 25°C with a 12 h light/dark light cycle. Colony sizes were measured by using ImageJ 1.53a .Fungal growth was assayed by inoculating spore suspension on the center of three different agar media. Spore germination and appressorium formation were detected in 96-well plates. Briefly, spores were collected from MS agar medium and the concentration was adjusted to 2 × 10eJ 1.53a . To deteCapsicum annuum cv. Hero, Fushimi amanaga and Groupzest. The fresh harvested fruits were washed with water and surface sterilized with 0.5% bleach and left to dry overnight. Fungal spores were collected from MS agar medium and the concentration was adjusted to 2 × 105 spores/ml. Spore suspension was dropped (5 μl/drop) on the fruit surface with dual inoculation, in which the wild type strain was inoculated on one side of the fruit and a transgenic strain was inoculated on the other site of the same fruit. The fruits were incubated in a growth chamber at 25°C with 12 h light/dark light cycle. At least three fruits having 3–5 inoculation sites were used for each strain in each inoculation. Lesion sizes were measured with Spot image analysis software  and the statistical analysis was performed by paired t-test at P < 0.05 using Statistical Package for the Social Sciences software, version 20 .Pepper fruits were used for pathogenicity assay, including Colletotrichum strains, multi-locus phylogenetic analysis with 174 fungal strains was performed. The results indicated that Coll-153, Coll-365, and Coll-524 all belong to the acutatum species complex  isolated from apple in the United States than Coll-365 and Coll-153  and two (0.9-kb and 5.1-kb) of the 54 scaffolds in Coll-524 did not exist in Coll-153 and Coll-365, respectively, and no genes were encoded in the two scaffolds. A total of 29 and 30 genes were annotated from Coll-153 and Coll-365 specific genome sequences, respectively, and 23 of them are homologs in both Coll-153 and Coll-365. None of these genes had traits related to pathogenicity when blasting to the PHI database.Genome mapping of Coll-153 and Coll-365 to Coll-524 was analyzed with CLC Genomic Workbench v.9.5.1 and provided the specified information of DNA insertion, deletion, removal, and Misc. difference in Coll-153 and Coll-365 . The resDNA insertion, deletion, removal, and misc. differences (SNP and MNP) occurring in Coll-153 or Coll-365 may affect the open reading frames (ORFs) of their genes. To understand the influence on ORFs, we used a simple mathematical method to detect ORF variation (ORF-V) for all ORFs in Coll-153 and Coll-365 as illustrated in Colletotrichum strains that are available in the NCBI database, the 14 genes appeared in almost all members of the acutatum species complex, except Coll-365  in each scaffold were further analyzed and the results were displayed in Coll-365 . Moreoveic genes .To understand the difference in orthology among the three strains, proteins were analyzed using OrthoFinder . OrtholoTo understand the variations in pathogenicity-related genes among the three strains, analyses of pathogenicity-related functional categories were performed. Six categories were used, candidate effectors, carbohydrate active enzymes (CAZymes), secondary metabolism clusters, transcription factor (TF), and enzymes in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and pathogen–host interaction (PHI) related genes. The results showed the three strains had very similar numbers of genes in various categories . When coColletotrichum strains with genomes available in the NCBI database. As shown in C. acutatum species complex (Coll-524 and C. scovillei TJNH1) carried all the 33 candidate effector genes, while one strain of this complex, C. acutatum 1, had 32 of the candidate effectors. However, two strains with phylogenetics closely related to Coll-524, C. fioriniae HC89 and HC91, only carried two of the 33 candidate effector genes. Among the 62 Colletotrichum strains, 27 did not carry any of the 33 candidate effectors and they were mainly in the species complexes graminicola, spaethianum, and gloeosporioides. Interestingly, none of the members of the graminicola species complex carried any of the 33 candidate effectors. Moreover, a total of 24 of the 33 candidate effectors were only found in the acutatum complex, and not in the other complexes.The gene variations of the six functional categories in scaffolds 17, 19, 20, and 22 in the three strains are summarized in The variations of PHI genes among the three strains in scaffolds 17, 19, 20, and 22 were found to mainly occur in scaffolds 19, 20, and 22, especially genes required for fungal full virulence in the PHI database. A total of 79 genes with functions related to reducing virulence were found to be partially or fully removed in Coll-365 and 71 of them were not in Coll-153 .N-glycan biosynthesis. Coll-524 carried more genes than Coll-153 and/or Coll-365 in the five pathways  , TranspoOrthogroup and ORF-V analysis revealed two sets of variations in gene composition of the three strains. To obtain comprehensive analysis of variation, additional analysis was conducted by blastn using Coll-524 genes against the genome sequences of Coll-153 and 365. A total of 219 genes from Coll-153 and/or 365 with less than 50% coverage to Coll-524 were identified and used with genes selected from the other three groups, orthogroup analysis (511 genes), ORF-V analysis (799 genes) and pathogenicity-related categories analysis, for further analysis .CsEF1, CsBGN, CsLAP, CsBZTF, and CsPLAA . CsGIP was shown to inhibit the germination of Coll-365 in this study (see below). Thus, it is named as germination inhibited protein (GsGIP). Genes encoding cytochrome P450 or FAD binding domain-containing protein were not selected because they belong to large gene families in Coll-524. The eight genes were analyzed by PCR to confirm their absence in the genome of Coll-153 and/or Coll-365 . Therefore, for Coll-365 transgenic strains carrying two closely linked genes, three or four of the four genes were generated , IX , and X  showed significantly enhanced growth on MS agar medium in comparison with their wild-type strain Coll-365, but still showed slightly slower growth than Coll-524  and Coll-524 . Inoculation assays conducted on Capsicum annuum cv. Fushimi-amanaga revealed that strains generated from transformation VII - X produced larger lesion sizes than wild-type Coll-365  in the Conserved Domains Database (CCD) of NCBI to COG1196. COG1196 is classified as a model that may span more than one domain and is the only member of the superfamily cl34174 in the CDD. The best hit of gene CsGIP in CDD is condensin subunit SMC4 (NP_013187.1) of Saccharomyces cerevisiae S288C. Condensin is a subunit of SMC  protein complexes that exist in all eukaryotes and play important roles in chromosome organization and dynamics  located within the 34-kb fragment at scaffold 17 were transferred into Coll-365 as individual genes or gene sets since they are closely linked. CsBZTF had a high expression level in axenic cultures and all infection stages. The other three genes were expressed in axenic cultures and the late infection stage, but genes CsPLAA and CsCZCP also had relatively high expression in the cuticle infection stage. These four genes did not influence the germination and appressorium formation of Coll-365. However, transgenic strains carrying one CsPLAA, three genes CsBZTF, CsCZCP, and CsPLAA, or four genes CsBZTF, CsCZCP, CsPLAA, and CsWDCP have similar colony sizes but are larger than the wild-type Coll-365, indicating that CsPLAA contributes to the growth enhancement of Coll-365. CsBZTF is a bZIP transcription factor and might be highly related to pathogenicity  can be found below: NCBI BioProject – D-KH, S-CC, M-HL, and M-CS contributed to the design of the experiments. S-CC designed and prepared the DNA and RNA materials for sequencing. D-KH performed all bioinformatic analyses and gene transformation as well as functional characterizations. Y-TC and C-YC assisted in sequence assembly and annotation. M-YL performed NGS sequencing. M-HL and M-CS supervised the experiments. D-KH, M-HL, and M-CS wrote the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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Narrowing a large set of features to a smaller one can improve our understanding of the main risk factors for in-hospital mortality in patients with COVID-19. This study aimed to derive a parsimonious model for predicting overall survival (OS) among re-infected COVID-19 patients using machine-learning algorithms.The retrospective data of 283 re-infected COVID-19 patients admitted to twenty-six medical centers  from 10 June to 26 December 2020 were reviewed and analyzed. An elastic-net regularized Cox proportional hazards (PH) regression and model approximation via backward elimination were utilized to optimize a predictive model of time to in-hospital death. The model was further reduced to its core features to maximize simplicity and generalizability.. In addition, the mortality rate among the intubated patients was 83.5%. Using the Kaplan-Meier approach, the OS (95% CI) rates for days 7, 14, and 21 were 87.5% (81.6-91.6%), 78.3% (65.0-87.0%), and 52.2% (20.3-76.7%), respectively. The elastic-net Cox PH regression retained 8 out of 35 candidate features of death. Transfer by Emergency Medical Services (EMS) , SpO2≤85% , increased serum creatinine , and increased white blood cells (WBC) count  were associated with higher in-hospital mortality rates in the re-infected COVID-19 patients.The empirical in-hospital mortality rate among the re-infected COVID-19 patients was 9.5%2≤85%), increased serum creatinine (more than 1.6 mg/dL), and increased WBC count (more than 8.5 (×109 cells/L)) reduced the OS of the re-infected COVID-19 patients. We recommend that future machine-learning studies should further investigate these relationships and the associated factors in these patients for a better prediction of OS.The results of the machine-learning analysis demonstrated that transfer by EMS, profound hypoxemia (SpOThe online version contains supplementary material available at 10.1186/s12889-021-12383-3. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease 2019 (COVID-19) first started in China in December 2019. It rapidly spread around the world and became a pandemic and a major health issue. It is associated with clinical symptoms . The medRecently, global concern over the possibility of re-infection with SARS-CoV-2 has risen considerably , 6. StudSo far, various studies have been conducted to explore the determinants of the overall survival (OS) of COVID-19 patients –17. EpidIn the study of time-to-event data (e.g. time to death or discharge), bigger sample sizes and more desired events are often preferable. Simulation studies have indicated that training multiple survival time models using traditional models with small sample size data can lead to bias in the estimation of the coefficients since the outcome events per candidate feature (OEPCF) are too few. Accordingly, the model will most probably have unstable predictions and a poor performance on new datasets –21. Amonelastic-net can be applied to a dataset to produce estimates of regression coefficients via adding a penalty term to the partial log-likelihood function. When combined with ML algorithms for feature selection we can get an externally validated parsimonious regression model [Generally, narrowing a large set of features to a smaller one can improve our understanding of the most important risk factors for in-hospital death in patients with COVID-19. The LASSO and on model .To the best of our knowledge, the prognosis and OS of patients with COVID-19 re-infection have not been determined so far. Hence, the current study aimed to derive a parsimonious regression model for predicting OS among re-infected COVID-19 patients. In this study, the elastic net ML algorithm (which has not been utilized for COVID-19 data so far) was used to optimize the prediction of time to in-hospital death.This retrospective cohort study was conducted on all inpatients with confirmed COVID-19 who were referred to 26 medical centers ) from 10 June to 26 December 2020. Their disease was confirmed by RT-PCR test. The inclusion criteria were patients with the age of ≥18 years who had previously recovered from COVID-19 disease but were re-infected. Patients with unknown last status  and high missing data were excluded from the study. Finally, a total of 283 cases were analyzed. The patients’ demographics characteristics and clinical and laboratory test findings available soon after admission to the hospital were extracted from the Health Information System (HIS) of SUMS.This study was conducted in accordance with the Declaration of Helsinki. Besides, it was approved by the Vice-Chancellor of Research and Technology (Grant No. 21237) as well as the Ethics Committee of SUMS (IR.SUMS.MED.REC.1399.337).. The patients’ OS probability was estimated using Kaplan-Meier (KM) curves and the different groups were compared using the non-parametric log-rank test [The qualitative features were presented as numbers and percentages and the quantitative data were presented as mean (±SD). The non-survivor and survivor groups were compared using independent sample t-test. The time interval from admission date to end of follow-up was regarded censored time if in-hospital death had not occurredank test .ℓelastic − net) can be formulated as follows:For large sample size data, the regression coefficients can be accurately estimated using traditional maximum likelihood technique , 24. In whereℓ is a non-regularized log partial likelihood function, while α and λ are tuning parameters which are data-dependent and some a priori values cannot be attributed to them. The ridge (α=0) and LASSO (α=1) regressions are specific cases of elastic-net regression [Here, gression , 25. MorThe major challenge is to determine these tuning parameters for which the cross-validated likelihood function of the model is maximum. The five-fold cross-validation (CV) approach was used in this study. To perform CV, the original dataset was randomly divided into five equal parts or folds. First, one fold was reserved and a separate model was trained on all the other folds. Then, the trained model was tested on the reserved fold and the partial likelihood deviance was calculated. After repeating this process and utilizing all the five folds as the test sets, the average of the five computed partial likelihood deviances was called the ‘CV error’ .glmnet” and “survival” packages in the R statistical software (version: 3.6.3) and “PROC PHREG” in SAS statistical software (version 9.2). The MedCalc software (version: 8.0.0.0) was also used to draw the ROC curve for continuous variables, as well as the area under the curve (AUC), 95% CI and p-value calculation.When the sample size is not large enough, instead of the traditional Cox regression, an alternative regularized regression can be used. In the current study, an elastic-net regularized Cox PH regression was employed to model time to in-hospital death in the re-infected COVID-19 patients. Similar to LASSO, the elastic-net algorithm performs feature selection by setting some regression coefficient estimates to zero. The features selected by the elastic-net algorithm were then entered into a standard non-regularized Cox PH regression to specify a baseline for comparison during model development. The backward elimination approach was used to reduce the number of features in the baseline model and to obtain a parsimonious one , 25. In The analyses were restricted to 283 patients re-infected with COVID-19 . Out of this number, 178 patients (63%) had underlying diseases (hypertension (28%), kidney diseases (14%), cardiovascular diseases (11%), diabetes mellitus (10%), and others (37%)). The statistics also demonstrated that about 70% of the patients used steroids including dexamethasone, hydrocortisone, and methylprednisolone as adjuvant therapy. With the mean (±SD) age of 52.2 (17.6) years, the empirical in-hospital mortality rate was 9.5%. The descriptive results also indicated that about 81.5% of the deaths occurred during the first 7 days after admission. In addition, the results showed that the in-hospital death rate among the intubated re-infected patients was 83.3%. More details of the baseline demographic characteristics and clinical and laboratory test findings are presented in Tables n=177, 62.5%) followed by lopinavir/ritonavir, branded as Kaletra , azithromycin , remdesivir , chloroquine , hydrocortisone , methylprednisolone , and favipiravir .Regarding drug treatment (steroids and antibiotics), the majority of the re-infected patients received dexamethasone , type of patient transfer (P<0.001), temperature (P=0.053), SpO2 (P<0.001), pulse rate (P=0.024), respiratory rate (P=0.022), intubation (P<0.001), and triage level (P<0.0001). Moreover, there was no significant difference in OS by gender (P=0.638)   and LASSO (α=1) regressions. The values of the tuning parameters α and λ were optimized by averaging five repetitions of five-fold CV to minimize the partial likelihood deviance error (α2 of ≤85% (coefficient=0.8145), intubated patients (coefficient=0.5699), and cases with triage level 1 (coefficient=0.5067). The features selected by the elastic-net regularized regression were then entered into the non-regularized Cox-adjusted PH model to specify a baseline for comparison during model approximation. The stepwise backward elimination method was used to convert the baseline regression model into a parsimonious one.The elastic-net regularized Cox PH model retained 8 out of 35 candidate features of death. The estimated shrunken coefficients for all the retained features are summarized in Table The results of the elastic-net regularized Cox regression as well as the hazard ratio (HR) (95% CI) of in-hospital death are shown in Table 2 of ≤85% , increased serum creatinine , and increased WBC count  were associated with higher mortality rates in the re-infected COVID-19 patients. In addition, the ROC curve analysis suggested that the cut-off values of 8.5 (×109 cells/L) for WBC count and 1.6 mg/dL for serum creatinine were the best to distinguish between patient’s OS  and creatinine: AUC=0.742  , SpOThe review of literature showed that no research has been done so far on the predictive determinants of overall survival among re-infected COVID-19 patients. Only the systematic review conducted by SeyedAlinaghi et al. was a comprehensive study which assessed the risk of COVID-19 re-infection . They foThe underlying diseases, clinical conditions, use of glucocorticoids, and secondary bacterial infection were identified as the independent risk factors of COVID-19 re-infection , 26, 27.Recent studies have reported that some patients who had recovered from COVID-19 had a positive PCR test result for the second time , 30–36. 2, intubation, and triage level (level 1 vs. others). The backward elimination method further reduced the regularized model to retain four features: type of patient transfer, SpO2, WBC count, and serum creatinine.Regularization algorithms such as elastic-net and LASSO can be used to perform feature selection and to improve the prediction accuracy by shrinking the coefficients towards zero . In thisSince no similar studies were found about the survival of re-infected COVID-19 patients, the results of this study were compared with those of the studies related to survival and the related risk factors in patients with COVID-19. The results of the current research showed that the empirical in-hospital mortality rate was 9.5%. Furthermore, the OS rates for days 7, 14, and 21 were obtained as 87.5, 78.3, and 52.2%, respectively, in the re-infected COVID-19 inpatients. These rates have been reported differently for COVID-19 patients in other studies , 15, 37.9 cells/L)) were associated with a higher mortality rate in re-infected COVID-19 patients. As compared with the surviving re-infected COVID-19 patients, the levels of creatinine were independent predictors of abnormal kidney function at the time of admission in the non-surviving re-infected COVID-19 patients. The higher in-hospital mortality rate was related to the higher concentration levels of creatinine (>1.6 mg/dL) in the patients, suggesting a worse renal function at the time of hospital admission. This finding is in line with previous studies which revealed that the concentration levels of creatinine were significantly higher among the COVID-19 patients who died [Regarding the laboratory findings at the time of admission, it was found that increased serum creatinine (more than 1.6 mg/dL) and increased WBC count (more than 8.5 (×10who died –40.2 <90%) increased the one-month mortality rate, this association was not significant [2 levels (greater than 85%) after oxygen supplementation were associated with reduced mortality. In fact, profound hypoxemia (SpO2≤85%) could have a harmful effect on the OS of re-infected COVID-19 patients, increasing the risk of mortality eight-fold. The findings of the present study were consistent with previous studies in which profound hypoxemia was associated with a higher in-hospital death rate [Moradi et al. assessed the risk of one-month mortality from COVID-19 since the time of admission. They found that increased NLR and increased WBC count were associated with a higher one-month death rate. Moreover, although hypoxemia , and high-sensitivity C-reactive protein (hs-CRP) as the survival predictors with the accuracy of more than 90%. In particular, it was revealed that high levels of LDH might have an independent harmful effect on the OS rate .We could not compare our results with other studies because we did not find any studies reporting transfer by EMS as an OS predictive factor. However, it could be said that the patients who were transferred to EMDs by EMS had a more severe status, increasing their mortality rate almost four-fold.This study had several limitations which should be mentioned. We could not find any similar study in the literature to compare our findings with. Therefore, we had to compare our results with studies which used general COVID-19 datasets for their analyses. The impossibility of examining the risk factors associated with re-infection as well as the difficulty of confirming the diagnosis of COVID-19 re-infection were two other limitations of the present study. Another limitation of this study was that it was conducted during the peak period of infection especially when the virus had an active transmission chain among the populations. Hence, our findings may vary in non-pandemic conditions.2≤85%), increased serum creatinine (more than 1.6 mg/dL), and increased WBC count (more than 8.5 (×109 cells/L)) reduced the OS of re-infected COVID-19 patients. Finally, we recommend that future machine-learning studies should further explore these relationships and the associated factors in these patients for a better prediction of OS.On the basis of the results it was concluded that transfer by the EMS, profound hypoxemia (SpOAdditional file 1: Appendix


Introduction: The results of studies comparing the characteristics of Internet gaming with those of Internet gambling have been controversial. We hypothesized that problematic web-based board gaming behaviors are associated with psychological and social interaction factors. We also hypothesized that non-problematic adolescent Internet gaming is a protective factor against problematic web-based board gaming and that problematic Internet gaming is a predictive factor for problematic web-based board gaming.Methods: We recruited 104 adults who reported engaging in web-based gaming. All participants were asked to complete the Problematic Web Board Gameplay Scale, Center for Epidemiologic Studies Depression Scale (CESD), State-Trait Anxiety Inventory (STAI), Adult Attention Deficit/Hyperactivity Disorder Self-Report Scale (K-AADHD), Family Environmental Scale (FES), Social Avoidance and Distress Scale (SADS), and questionnaires on their web-based board gaming patterns and Internet gaming history.Results: Problematic web-based board gamers showed a lower history of adolescent Internet gaming but a greater rate of problematic Internet gaming compared with healthy web-based board gamers. Moreover, problematic web-based board gamers showed an increase in CES-D, STAI, K-AADHD, and SADS scores but decreased FES scores compared with healthy web-based board gamers. Joblessness; less experience as an Internet gamer; a history of problematic Internet gaming; higher CES-D, STAI, and K-AADHD scores; and lower FES scores were significant predictors of problematic web-based board gaming.Discussion: Psychological, social, and environmental factors can positively influence problematic Web-based board gaming. Healthy Internet gaming during adolescence may play a preventive role in adult problematic web-based board gaming. However, because adolescent problematic Internet gaming tends to lead to problematic web-based board gaming, measures should be taken to prevent it. Internet gaming is a popular leisure activity worldwide . In KoreSeveral factors have been linked to problematic Internet gaming –17. For Web-based board games are real-time board games played through online web browsers  age from 20 to 60 years; (2) engagement in web-based board gaming  more often than 1 day a week, for a period of more than 1 year, on a legal online site; (3) an official report of web-based board gaming activity, supplied by the web-based board game company at the customer's request; and (4) no history of psychiatric disorders, including substance abuse. The study protocol was approved by the institutional review board of Chung Ang University. Informed consent was obtained from all participants and was confirmed by the board.EmbrainThe demographic data collected by the study included age, gender, education year, job status, economic status, web-based board game pattern, and history of Internet game play.The pattern of Internet gaming was assessed using two questionnaires: internet game play time (hour/day) and genre of Internet game. The first question, regarding the participant's Internet game play history, asked, “When you were an adolescent, did you engage in internet gaming at least once a week for 1 year?” The one-week frequency and one-year duration mentioned in the question were based on the IGD research  and diagWe estimated depressive symptoms using the Center for Epidemiologic Studies Depression Scale (CESD). The CESD is a 20-item, four-point self-report instrument . The totFamily cohesion was estimated using the Family Environmental Scale (FES). Higher FES scores indicate better family cohesion. The internal consistency of the scale was 0.86 , 39. We We used the Problematic Web Board Gameplay Scale  to defint-test or χ2 test. Web-based board gaming patterns and Internet gaming histories were analyzed using independent t-tests and the χ2 test. Scores on the psychological and interaction scales were analyzed using independent t-tests.Differences in demographic data between problematic web-based board gamers and healthy web-based board gamers were analyzed using an independent We used hierarchical logistic regression analysis to confirm whether the study's variables could predict statistically significant variance in the dependent variable, for which problematic web-based board gaming was coded as 1, and healthy web-board gaming was coded as 0. Regarding the independent variables, the following discrete set of hierarchical variables was added: demographic factors  for model 1, model 1 + history of Internet gaming (history of Internet game play and problematic Internet game play) for model 2, model 2 + psychological status  for model 3, and model 3 + interaction factors  for model 4.The overall fit of each step of the logistic regression model was evaluated with χ2-values (model χ2 and step χ2), while the goodness-of-fit was evaluated with −2 log likelihood. The χ2 values showed the improvement observed in the model, with the predictors relative to the constant-only model or the model preceding the current model. We also evaluated the practical usefulness of each model using tables of classification accuracy to determine the relative success of each model in predicting the correlations with improved golfers. In addition, Nagelkerke's R2 was assessed as an approximate estimate of the amount of variance in the dependent variable accounted for by the model. Wald statistics were used to test whether each individual factor had a significant relationship with improved golfers. When a significant relationship was detected by the Wald test, the interpretation of the coefficient was followed by a determination of the odds ratio—that is, the ratio of the probability that the event (problematic web-based board gaming) would occur to the probability that it would not.Problematic web-based board gaming was associated with older age  and joblessness  compared with healthy web-based board gamers. There were no significant differences in gender, years of education, or socioeconomic status between the two groups see .Problematic web-based board gamers showed higher Problematic Web Board Gameplay Scale scores (26.6 ± 3.9 vs. 17.9 ± 4.3), number of logins (2.2 ± 1.8 vs. 1.3 ± 1.5), and play time (1.6 ± 0.8 vs. 1.3 ± 0.6 hours/day) compared with healthy web-based board gamers. There was no significant difference in the game-winning rate between the two groups see .Problematic web-based board gamers showed a shorter history of adolescent Internet gaming  but a higher rate of problematic Internet gaming  compared with healthy web-based board gamers see . In addiProblematic web-based board gamers showed higher scores on the CES-D , STAI (85.9 ± 19.9 vs. 76.5 ± 16.5), and K-AADHD (15.6 ± 7.5 vs. 6.6 ± 5.1) scores compared with healthy web-based board gamers see . ProblemA Durbin–Watson test indicated that there was no autocorrelation in the data. Of the four models employed, all were significantly associated with problematic web-based board gaming. Considering its highest step χ2 value and the improved classification accuracy, adolescent Internet gaming history was the strongest factor for problematic web-based board gaming among all the domains. Considering its highest model χ2 value and the improved classification accuracy, Model 4, which included all domains, predicted problematic web-based board gaming most strongly among the models.p < 0.01) and Nagelkerke's R2  indicated that the model was good enough to predict problematic web-based board gaming. When we examined the practical usefulness of the model based on classification accuracy, five variables in Model 1 enhanced the prediction accuracy of the group membership of the dependent variable to 73.1%. The step χ2 value  showed that demographic factors were the main predictive factors for problematic web-based board gaming. In Model 2, the χ2  and Nagelkerke's R2  indicated that the model was good enough to predict problematic web-based board gaming. The seven variables in Model 2 enhanced the prediction accuracy of the group membership of the dependent variable by 84.8%. The step χ2 value  showed that the factors of pattern of internet game play were the main predictive factors for problematic web-based board gaming. In Model 3, the χ2  and Nagelkerke's R2  indicated that the model was good enough to predict problematic web-based board gaming. Ten variables in Model 3 enhanced the prediction accuracy of the group membership of the dependent variable to 89.4%. The step χ2 value  showed that the factors of psychological status were the main predictive factors for problematic web-based board gaming. In Model 4, the χ2  and Nagelkerke's R2  indicated that the model was good enough to predict problematic web-based board gaming. The 12 variables in Model 4 enhanced the prediction accuracy of the group membership of the dependent variable to 94.14%. The step χ2 value  showed that the interaction factors were the main predictive factors for problematic web-based board gaming (see In Model 1, the χ2 (21.9, ming see .The results of the Wald's statistics for all independent variables indicated that joblessness; less experience of Internet gaming; problematic Internet gaming history; higher scores on the CES-D, STAI, and K-AADHD; and lower scores on the FES were significant predictors of problematic web-based board gaming see .Problematic web-based board gaming was associated with a shorter history of adolescent Internet gaming but a greater rate of problematic Internet gaming compared with healthy web-based board gamers. Problematic web-based board gaming was associated with higher CES-D, STAI, K-AADHD, and SADS scores but lower FES scores than healthy web-based board gaming. Overall, joblessness; less experience with Internet gaming; a history of problematic Internet gaming; higher scores on the CES-D, STAI, and K-AADHD; and lower FES scores were significant predictors of problematic web-based board gaming.2 values, this study found that demographic factors could be significant predictive factors for problematic web-based board game play. Of the demographic domains, such as IGD (Considering the step χh as IGD , 36, proh as IGD . Kim et h as IGD .Of the four domains, Internet gaming pattern was found to be the most crucial for problematic web-based board gaming. Considering the negative beta value of Internet game play history, experience of adolescent Internet gaming would be negatively correlated with adult problematic web-based board gaming. Considering its positive beta value, history of problematic adolescent Internet gaming was associated with adult problematic web-based board gaming. The beta value of the regression analysis was reflected in the slope of the regression line . Taken tThese results offer new insights into the prevention of problematic web-based board gaming. In contrast to our results, several previous studies have demonstrated the risks of early exposure to Internet gaming or gambling –46. The Several studies have shown that, for complicated reasons, a problematic Internet gaming history could be a higher risk for problematic Internet gaming or gambling than exposure to Internet gaming or gambling itself , 45. KarWe have already shown that problematic web-based board gaming may be linked to users' psychological and social problems . SimilarThis study has several limitations. First, the sample size was relatively small and had a cross-sectional design; therefore, the results may have limited generalizability. Future studies should consider a longitudinal design with a larger population. Second, we did not examine adolescent web-based board gaming history or adult Internet gaming history. There may be correlations between these two factors; however, this study recruited only web-based board gamers and collected data on their Internet gaming. Thus, further studies are required to classify the characteristics of each group. Finally, the study did not assess tobacco information details. Tobacco habits are known to be associated with gambling disorder. Future studies should assess the relationship between tobacco habits and web-based board gameplay.The results of this study showed that psychological, social, and environmental factors can positively influence problematic web-based board gaming. Healthy Internet gaming during adolescence may play a preventive role against problematic web-based board gaming during adulthood. However, measures should be taken to prevent problematic adolescent Internet gaming because it tends to lead to problematic web-based board gaming.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Institutional Review Board of the Chung Ang University. The patients/participants provided their written informed consent to participate in this study.SB and DH contributed to the conception of the study. DH and KM contributed to the study methodology. SK contributed to the formal analysis of the study. HR contributed to the investigation of this study, preparation of the original draft, review, and editing of the manuscript. DH supervised the study. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


This study aimed to establish a nomogram to predict the overall survival (OS) of patients with bladder cancer (BC) by ferroptosis-related long noncoding RNAs (FRlncRNAs) signature.  We obtained FRlncRNAs expression profiles and clinical data of patients with BC from the Cancer Genome Atlas database. The patients were divided into the training set, testing set, and overall set. Lasso regression and multivariate Cox regression were used to establish the FRlncRNAs signature, the prognosis of each group was compared by Kaplan–Meier (K-M) analysis, and the receiver operating characteristic (ROC) curve evaluated the accuracy of the model. The Gene Set Enrichment Analysis (GSEA) was used for the visualization of the functional enrichment for FRlncRNAs. The databases of GEPIA and K-M Plotter were used for subsequent functional analysis of major FRlncRNAs. P < 0.001). Combining the FRlncRNAs signature and clinicopathological factors, a predictive nomogram was constructed. The nomogram can accurately predict the overall survival of patients and had high clinical practicability. The GSEA analysis showed that the primary pathways were WNT, MAPK, and cell-matrix adhesion signaling pathways. The major FRlncRNAs (MAFG-DT) were associated with poor prognosis in the GEPIA and K-M Plotter database.  Thirteen prognostic FRlncRNAs  were identified to be significantly different, constituting an FRlncRNAs signature. Patients with BC were divided into low-risk group and high-risk group by this signature in the training, testing, and overall sets. K-M analysis showed that the prognosis of patients in the high-risk group was poor and the difference in the subgroup analyses was statistically significant. ROC analysis revealed that the predictive ability of the model was more accurate than traditional assessment methods. A risk score based on FRlncRNAs signature was an independent prognostic factor for the patients with BC (HR = 1.388, 95%CI = 1.228–1.568,  Thirteen prognostic FRlncRNAs and their nomogram were accurate tools for predicting the OS of BC, which might be molecular biomarkers and therapeutic targets. Bladder cancer (BC) is one of the most common cancers worldwide, with nearly 430,000 newly diagnosed patients each year . ApproxiFerroptosis, as iron-dependent programmed cell death, is mainly characterized by lipid peroxidation . With thLong noncoding RNAs (lncRNAs) were found to play a wide range of roles in a variety of important biological processes, including cell proliferation and differentiation, regulation of gene expression, RNA translation, and regulation of microRNAs , 15. In https://portal.gdc.cancer.gov/) database. The inclusion criteria were as follows: (a) patients were diagnosed as BC; (b) patients had complete lncRNA expression profiles and clinical data. According to the inclusion criteria, 414 patients were included in our study. In addition, the clinical data  were also downloaded from TCGA. We excluded the patients who had a follow-up time of less than 30 days and incomplete RNA-seq and clinical data. The study did not need the approval of the ethics committee because the data involved in this study were all from TCGA database and strictly complied with TCGA guidelines (http://cancergenome.nih.gov/abouttcga/policies/publicationguidelines).We followed the methods of Dr. Zhou et al. . We obtahttp://www.gsea-msigdb.org/gsea/index.jsp) was used to download the list of 60 ferroptosis-related genes (FRGs), of which 59 FRGs were expressed in BC. Pearson analysis was used to estimate the correlation degree between lncRNAs and FRGs. The square of correlation coefficient ∣R2∣> 0.3, and P < 0.001 was considered as FRlncRNAs. Finally, 1,810 FRlncRNAs were selected.We obtained the profiles of lncRNAs from all the RNA-seq data and standardized the RNA-seq data by log2 transformation. A total of 14,142 lncRNAs were isolated from the TCGA-BLCA dataset. The Gene Set Enrichment Analysis  regression. We visualized the coexpression of FRlncRNAs and FRGs using Cytoscape 3.6.0 and the correlation between FRlncRNAs using “igraph package” and “reshape2 package” in R software. Then, the results of lasso regression were included in the multivariate Cox regression model to establish the risk score of each patient. A risk score (∑i=1nβi∗(expression of lncRNAi)) was established by the expression level of FRlncRNA multiplied by regression coefficient (β). Based on the median of risk score, the patients were divided into high-risk group and low-risk group, and the survival rates between the two groups were compared by log-rank test.We divided 395 patients into training set (197 cases) and testing set (198 cases) according to a ratio of 1 : 1. The basic characteristics of each group are shown in In addition, the same formula was used to calculate the risk score of each patient in the testing set and overall set to verify the stability of the established model. The Kaplan-Meier (K-M) curve was conducted to analyze the survival outcomes of each set. The receiver operating characteristic (ROC) curve and its area under the curve (AUC) value were applied to evaluate the specificity and sensitivity of the established model by “ROC package” in R software.An independent prognostic model was established by Cox regression analysis. The 1 -, 3 -, and 5-year survival rates were predicted by establishing nomogram. The stability of the model was evaluated by the index of concordance (C-index), calibration curves, and ROC curves. The basic characteristics of patients were included in the multivariate Cox regression to determine whether the risk score was an independent predictor of prognosis.http://www.broadinstitute.org/gsea/index.jsp). The study accessed the functional enrichment of FRlncRNAs and visualized the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to ferroptosis. In the enrichment analysis, a two-sided P value of <0.05 was considered significant.The functional enrichment of FRlncRNAs was explained by the Gene Set Enrichment Analysis (GSEA) (http://gepia.cancer-pku.cn/) database contained RNA-seq and clinical data compiled by TCGA and GTEx databases after standardized transformation. The K-M Plotter database  included RNA-seq and prognostic data of 405 BLCA patients. The above two databases were used to verify the relationship between major FRlncRNAs and patient's prognosis.The Gene Expression Profiling Interactive Analysis  was used for statistical analysis. Statistical tests were two-sided, and studies were considered statistically significant when P < 0.05). Then, we identified 29 FRlncRNAs by lasso regression  + (0.0550∗MAFG-DT) + (0.1824∗AL049840.3) + (0.1928 ∗ AL136084.3) – (0.3582∗OCIAD1-AS1) – (0.3362∗AC062017.1) – (0.2606∗ AC008074.2) – (0.2419∗AC018653.3) – (0.2375∗ AL031775.1) – (0.1942∗USP30-AS1) – (0.1094∗ LINC01767) – (0.0730∗ AC132807.2) – (0.0662∗AL354919.2).The flowchart of this research is shown in  Figures . By multP < 0.001)  and high-risk group (98 cases) based on the median of risk scores. The K-M curve showed a shorter overall survival (OS) in the high-risk group compared with the low-risk group (< 0.001) . Then, t< 0.001) . The hea< 0.001) . The sca< 0.001) . In addi< 0.001) . The AUC< 0.001) . Besides< 0.001) . In shorP < 0.001) (P < 0.001)   and over< 0.001) , and the< 0.001)  and over< 0.001)  for the < 0.001)  and over< 0.001) . Besides< 0.001) . Also, t< 0.001) . These rP < 0.001, P < 0.001, Based on the result of univariate Cox regression in the overall set, the risk score and stage were independent prognostic indicators in patients with BC, in which the HR of risk score was 1.414 , age (≤65 years and >65 years), stage (I-II and III-IV stages), T stage (T1-2 stage and T3-4 stage), and N stage (N0 stage and N1-3 stages).P < 0.05)    via multivariate Cox regression and lasso regression. K-M curve showed that the OS of patients with high-risk score were shorter than those of patients with low-risk score. In addition, the ROC curve proved that the 13 FRlncRNAs signature was highly sensitive and specific prognostic markers in BC. Besides, this result was further verified in the testing set and overall set. The 13 FRlncRNAs' signature was also associated with poor OS of BC patients in different subgroups, especially in age, gender, AJCC stage, T stage, and N stage. Next, a nomogram was used to count the risk score and can predict the OS of patients. The calibration curve showed that the signature had a higher sensitivity and clinical applicability than the traditional standard. Then, we established an FRlncRNA-mRNAs coexpression network to analyze the effect of the 13 FRlncRNAs' signature. And we also analyzed the correlation between 13 FRlncRNAs. The GSEA analysis revealed that signaling pathways such as WNT, MAPK, ERBB, cell-matrix adhesion, and positive regulation of cell division were significantly enriched in the high-risk group. Finally, we verified the major FRlncRNAs in two external databases. The results showed that the expression of MAFG-DT was higher in BC tissues, but with the increase of the stage, the expression of MAFG-DT also increased, and there was a significant correlation with survival outcomes. Correlation analysis found that MAFG-DT and protein-coding genes  were obviously related.Currently, multiple FRlncRNAs have been reported to be associated with poor prognosis in a variety of tumors. Among them, LINC00942 exerts its functions as an oncogene in promoting METTL14-mediated m6A methylation and regulating the expression and stability of its target genes CXCR4 and CYP1B1 in breast cancer (BRCA) initiation and progression, which provides new targets and crosstalk m6A epigenetic modification mechanism for BRCA prevention and treatment . Six FRlAs a major FRlncRNA, MAFG-DT is a tumorigenic lncRNA in a variety of cancers. Firstly, MAFG-DT as a part of lncRNAs signature of tumor-infiltrating B lymphocytes had some predictive value for the survival outcomes and immunotherapy response of patients with antiprogrammed death-1 (PD-1) therapy and added significant predictive power to current immune checkpoint gene markers . Next, LCurrently, multiple studies have highlighted the role of lncRNAs in the pathogenesis of BC. These lncRNAs were downregulated or upregulated during the origin, proliferation, and migration of BC. Therefore, it is very necessary to clarify the physiological roles of lncRNAs and their contributions to the development and progression of BC. For example, lncRNAs can contribute to mRNA degradation and failure of protein translation by mediating posttranscriptional gene silencing . In addiFerroptosis can synergistically enhance antitumor activity in combination with immune checkpoint inhibitors (ICIs), even in ICI-resistant types . CurrentFerroptosis, as a new form of cell death, may provide a new direction for tumor therapy. However, many key questions remain unresolved, such as how ferroptosis intersects with other cell deaths and host immunogenicity is less well studied. Therefore, this study explored ferroptosis-related biomarkers that can be used to predict BC prognosis, which may provide references for therapeutic modalities of cancer. However, the current study has some weaknesses. First, the data source of this analysis was single, and the amount of data included was small, so the results may have some bias. Second, the study was retrospective, and prospective studies may be needed to demonstrate the prognostic function of FRlncRNAs. Third, to further validate the stability and accuracy of this prognostic model, our established prognostic model needs further analysis in other independent cohorts. Fourth, relevant functional experiments should be performed to further analyze the underlying molecular mechanisms by which FRlncRNAs affect the development and progression of BC.The coexpression network of FRlncRNA-mRNA provided a valuable source for revealing the function of FRlncRNAs in BC. Thirteen FRlncRNAs were considered to be significantly associated with OS of patients with BC. An FRlncRNAs signature that was composed of thirteen FRlncRNAs was used to differentiate patients at different risks, and it was a significantly independent factor for patients with BC. Therefore, the thirteen FRlncRNAs and their signature might be molecular biomarkers and therapeutic targets for patients with BC.